CompletedNCT06617403

Can Pre-operative Characteristics Predict Failure of Supraglottic Airway to Tracheal Tube? A Machine Learning Algorithm (ERICA)

Sponsor: University Hospital Ulm

Trial Details

Condition	Anesthesia, General, Postoperative Complications, Laryngeal Masks, Treatment Failure
Intervention	non
Status	Completed
Participants	44,000
Est. Completion	30 Nov 2024
Last Updated	13 May 2026

Primary Outcome

Risk of unplanned SGA conversion

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: * Adult patients (≥18 years) receiving general anaesthesia for non-cardiac surgery with a supraglottic airway device Exclusion Criteria: * None

Trial Sites

Countries

Germany

View Registry Entry

Related Analysis

ERICA Study Develops AI Model to Predict Supraglottic Airway Failure — 44,000-Patient Analysis Offers New Risk Stratification Tool

German researchers analysed 44,000 patients to develop a machine learning algorithm predicting supraglottic airway failure. The ERICA study offers new risk stratification tools for anaesthetists planning airway management strategies.

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